Author(s)

Shaofei Wang, Kaiji Sato, Toshiharu Kagawa

Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Yokohama, Japan.

Pneumatic artificial muscles (PAMs) currently possess a high power-to-weight ratio, a high power-to-volume ratio, and a high degree of safety. They have therefore been applied to many power assist devices and positioning mechanisms such as bionic robots, welfare devices, and parallel manipulators. However, the significant nonlinear characteristics of PAM mechanisms limit their positioning accuracies. The accuracies are generally lower than 5 μm, which preclude the PAM from precision systems. Nevertheless, enhancing the positioning accuracy is desired to extend the application fields of PAMs. This study aims to clarify a practical controller design method to achieve the precise positioning of PAM systems. As the first step of this research, a linear motion mechanism with a pair of McKibben PAMs was constructed and a conventional dynamic model for this system is introduced. The dynamic model is used to explain the basic characteristics of the PAM mechanism and discuss the necessary characteristics for precise positioning. Then open-loop step and sinusoidal responses of the PAM mechanism were examined by experimental and simulated results. Next, for precise positioning, the practical controller design procedure is discussed and determined based on the measured open-loop responses. The proposed controller design procedure can be easily implemented into PAM mechanisms without an exact dynamic model. The positioning performance of such a system was experimentally evaluated. The experimental results show that although the positioning accuracy depends on the target position, the positioning error is lower than 1 μm even in the worst case and the positioning resolution can be set to 0.5 μm.

Precision, Positioning, McKibben Pneumatic Muscle, Pneumatic Artificial Muscle, Accuracy

Wang, S. , Sato, K. and Kagawa, T. (2014) Precise Positioning of Pneumatic Artificial Muscle Systems. Journal of Flow Control, Measurement & Visualization, 2, 138-153. doi: 10.4236/jfcmv.2014.24016.